Model comparison
Amazon Nova Lite vs DeepSeek-R1
DeepSeek-R1 is the stronger model overall, scoring 42.3 to 31.9 on the Noometry Index. Amazon Nova Lite costs 8.7× less per token, which makes it the better buy when DeepSeek-R1's lead doesn't matter for your workload.
Last verified . 31 shared benchmarks.
DeepSeekSummary
- They share 31 benchmarks with published results for both. Amazon Nova Lite scores higher in 1 category and DeepSeek-R1 in 7 categories; 7 gaps are clear of the uncertainty.
- The widest gap is in writing & preference, where DeepSeek-R1 leads 61.4 to 42.1.
- The biggest single-benchmark swing is LiveBench Reasoning: 36.7% for Amazon Nova Lite and 83.2% for DeepSeek-R1.
- Amazon Nova Lite is cheaper at $0.06 / $0.24 per million input/output tokens, against $0.50 / $2.15 for DeepSeek-R1.
- Amazon Nova Lite accepts more context: 300K tokens versus 164K.
Side by side
| Amazon Nova Lite | DeepSeek-R1 | |
|---|---|---|
| Provider | Amazon | DeepSeek |
| Noometry Index | 31.9 | 42.3 |
| Released | 2024-12-03 | 2025-01-20 |
| Weights | Proprietary | Proprietary |
| Context window | 300K | 164K |
| Max output | 10K | 64K |
| Input $ / M tokens | $0.06 | $0.50 |
| Output $ / M tokens | $0.24 | $2.15 |
| Results tracked | 34 | 52 |
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Category by category
Coding DeepSeek-R1 leads
Amazon Nova Lite: 32.5 (#270), DeepSeek-R1: 46.3 (#68)
| Benchmark | Amazon Nova Lite | DeepSeek-R1 |
|---|---|---|
| LiveBench Coding | 27.5% | 66.7% |
| LMArena Coding | 1239 | 1427 |
| ALE-Bench | 236.25 | 804.12 |
| Aider Polyglot | — | 71.4% |
| SciCode | — | 35.7% |
| WeirdML | — | 41.6% |
| AlgoTune | — | 1.7 |
Agentic & Tool Use Not comparable
Amazon Nova Lite: —, DeepSeek-R1: 30.7 (#75)
| Benchmark | Amazon Nova Lite | DeepSeek-R1 |
|---|---|---|
| DeepResearch Bench | — | 35.1% |
| BALROG | — | 34.9% |
| METR Time Horizons | — | 53.8% |
Reasoning Too close to call
Amazon Nova Lite: 19.3 (#260), DeepSeek-R1: 18.6 (#278)
| Benchmark | Amazon Nova Lite | DeepSeek-R1 |
|---|---|---|
| LiveBench Reasoning | 36.7% | 83.2% |
| LMArena Hard Prompts | 1220 | 1416 |
| LiveBench Data Analysis | 37.2% | 69.8% |
| LiveBench | 36.4% | 71.6% |
| ARC-AGI-2 | — | 1.3% |
| SimpleBench | — | 40.8% |
| Kagi LLM Benchmark | — | 69.4% |
| ARC-AGI-1 | — | 21.2% |
| CritPt | — | 1.1% |
| Epoch Capabilities Index | — | 141.29 |
| ForecastBench | — | 60 |
Math DeepSeek-R1 leads
Amazon Nova Lite: 27.8 (#247), DeepSeek-R1: 43.8 (#79)
| Benchmark | Amazon Nova Lite | DeepSeek-R1 |
|---|---|---|
| Omni-MATH | 23.3% | 42.4% |
| LiveBench Math | 36.7% | 80.7% |
| LMArena Math | 1227 | 1400 |
| OTIS Mock AIME 2024-2025 | — | 66.4% |
| MATH Level 5 | — | 96.6% |
Knowledge DeepSeek-R1 leads
Amazon Nova Lite: 26.3 (#259), DeepSeek-R1: 44.5 (#87)
| Benchmark | Amazon Nova Lite | DeepSeek-R1 |
|---|---|---|
| MMLU-Pro | 60% | 79.3% |
| Vectara Hallucination Rate | 6.1% | 11.3% |
| GPQA (HELM) | 39.7% | 66.6% |
| LMArena Expert | 1201 | 1394 |
| GPQA Diamond | — | 76.3% |
| Humanity's Last Exam | 3.6% | — |
| Confabulations | — | 12.7% |
| MMLU | 77% | — |
Multimodal Not comparable
Amazon Nova Lite: 25.5 (#123), DeepSeek-R1: —
| Benchmark | Amazon Nova Lite | DeepSeek-R1 |
|---|---|---|
| LMArena Vision | 990 | — |
Multilingual DeepSeek-R1 leads
Amazon Nova Lite: 38.0 (#232), DeepSeek-R1: 52.4 (#85)
| Benchmark | Amazon Nova Lite | DeepSeek-R1 |
|---|---|---|
| LMArena Non-English | 1208 | 1412 |
| LMArena Chinese | 1225 | 1442 |
| LMArena French | 1237 | 1417 |
| LMArena German | 1229 | 1404 |
| LMArena Japanese | 1153 | 1391 |
| LMArena Korean | 1153 | 1360 |
| LMArena Russian | 1216 | 1423 |
| LMArena Spanish | 1226 | 1411 |
Instruction Following DeepSeek-R1 leads
Amazon Nova Lite: 59.3 (#255), DeepSeek-R1: 72.0 (#143)
| Benchmark | Amazon Nova Lite | DeepSeek-R1 |
|---|---|---|
| LiveBench Instruction Following | 54.1% | 80.5% |
| IFEval | 77.6% | 78.4% |
| LMArena Instruction Following | 1205 | 1382 |
Long Context DeepSeek-R1 leads
Amazon Nova Lite: 37.4 (#217), DeepSeek-R1: 45.4 (#36)
| Benchmark | Amazon Nova Lite | DeepSeek-R1 |
|---|---|---|
| LMArena Longer Query | 1234 | 1391 |
| Fiction.LiveBench | — | 75% |
Writing & Preference DeepSeek-R1 leads
Amazon Nova Lite: 42.1 (#237), DeepSeek-R1: 61.4 (#88)
| Benchmark | Amazon Nova Lite | DeepSeek-R1 |
|---|---|---|
| LMArena Text | 1229 | 1428 |
| LMArena Creative Writing | 1197 | 1405 |
| WildBench | 75% | 82.8% |
| LMArena Multi-Turn | 1199 | 1405 |
| LiveBench Language | 25.9% | 48.5% |
| Short-Story Creative Writing | — | 83% |
| EQ-Bench Creative Writing | — | 1500 |
Frequently asked questions
Is Amazon Nova Lite better than DeepSeek-R1?
DeepSeek-R1 is the stronger model overall, scoring 42.3 to 31.9 on the Noometry Index. Amazon Nova Lite costs 8.7× less per token, which makes it the better buy when DeepSeek-R1's lead doesn't matter for your workload.
Which is cheaper, Amazon Nova Lite or DeepSeek-R1?
Amazon Nova Lite is cheaper. It lists at $0.06 per million input tokens and $0.24 per million output tokens; DeepSeek-R1 lists at $0.50 and $2.15.
Is Amazon Nova Lite or DeepSeek-R1 better for coding?
DeepSeek-R1 scores higher on coding benchmarks: 46.3 versus 32.5 in the Noometry coding category.
Which has the bigger context window?
Amazon Nova Lite does, with 300K tokens against 164K.
How many benchmarks do Amazon Nova Lite and DeepSeek-R1 share?
31 benchmarks have published results for both models. Amazon Nova Lite has 34 scored results on Noometry and DeepSeek-R1 has 52.